大数据和集体智慧

M. Ivanović, Aleksandra Klašnja-Milićević
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引用次数: 1

摘要

如今,大数据的产生和积累是一个在各种情况和场景下不可避免的过程。智能环境和传感器的多样化来源,以及人类创造的内容,促成了大数据的巨大规模和特征。为了理解数据,分析和使用这些数据,越来越多高效的算法被不断开发出来。尽管如此,这些算法的有效性取决于大数据的具体性质:模拟、嘈杂、隐式和模糊。与此同时,还有一个不可避免的科学领域——集体智慧。它代表了相互连接的智能集体解决具体问题的能力,比单个智能单独解决问题的能力更有效。本文概述了近年来大数据和集体智能研究领域的研究成果。最后,讨论了这两个领域共同方向的前景和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big data and collective intelligence
Nowadays the creation and accumulation of big data is an unavoidable process in a wide range of situations and scenarios. Smart environments and diverse sources of sensors, as well as the content created by humans, contribute to the big data's enormous size and characteristics. To make sense of the data, analyse and use these data, more and more efficient algorithms are being developed constantly. Still, the effectiveness of these algorithms depends on the specific nature of big data: analogue, noisy, implicit, and ambiguous. At the same time, there is the unavoidable scientific area of collective intelligence. It represents the capability of interconnected intelligences to collectively and more efficiently solve concrete problems than each individual intelligence would be able to do on its own. The paper presents an overview of recent achievements in big data and collective intelligence research areas. At the end, the perspectives and challenges of the common directions of these two areas will be discussed.
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